How to Turn Energy Data Into Action

Today the energy supply market is more predictable than ever. The recent data ‘explosion’ in the industry provides a critical resource for forecasting and managing commodity costs, particularly in the crude oil and carbon pricing sectors.

The wider energy ecosystem, however, is becoming more complex as it tackles new challenges in productivity and usage, especially with the rapid increase in renewable and distributed generation. Those firms that can utilize data to understand how they can better integrate with the energy market will be best placed to extract the value from emerging opportunities and reap the benefits in the long run.

Four top tips to overcome market complexity and find the value in energy data to become more efficient and sustainable are outlined below.

Forward thinking with data

More data is available today than ever before. Advances in sensing technology and the increase in connectivity has led to an overwhelming amount of raw data being readily available to those enterprises than can utilize it. For example, the technology giant Microsoft, is able to process over 500 million data transactions every 24 hours from 125 buildings in its smart campus.

Technologies such as smart metering, have dramatically increased the volume of data available. A 15-minute interval smart meter can, on average, conduct 525,000 readings per day and with the world expected to house 602.7 million of these meters in 2016, that calculates to more than 316 trillion data readings every single year.

This exponential growth of data in the energy market, particularly in the oil sector, means those that are able to use this data in the correct way will have the edge in forecasting energy outcomes and future oil prices.

It is now clear that there is a real opportunity for firms to make better business decisions around energy. They are now able to create revenue by generating and selling energy or by participating in demand response schemes. For example, this summer the National Grid is to pay firms to use power. Under the scheme, companies will conduct some operations at night or at midday when there is a lot of electricity generated from wind farms and solar power plants.

This is made possible by the ability to forecast market drivers and build different scenarios using data, detailed analytics and raw economics.Those firms that elect to observe the market passively are failing to take advantage of new opportunities. Like anything else, the competitive edge will lie with those firms that can adapt the quickest, and benefit from new opportunities.

By harnessing data and putting it to use, organizations will be able to turn an internal data challenge into a market opportunity rapidly.

Be ahead of changes

Organizations should aim to harness industry knowledge before it is widespread. The ability to use this knowledge to mitigate risks and be more adaptable to new requirements will put them ahead of the competition and allow them to observe sustainability benefits of a higher degree.

For example, cap and trade is an environmentally and economically sensible approach to controlling greenhouse gas emissions. Governments in particular are turning to this approach in order to keep a handle on global emissions. Given this, businesses have no choice but to become involved in such methods. Those that best understand legislative obligations and the impact of data will be the ones to reap the benefits and get ahead of the renewable curve.

Finding a way to use energy data to project spend, identify future market forces and keep an eye on political developments will allow organisations to harness the knowledge of the factors driving their particular industry and market.

Using this data will also provide enterprises with additional market opportunities, and give them the ability to quickly sort through and identify viable and costly options. It will also help business owners to determine a roadmap to sustainability through forecasting.

Collaborate

Bringing business units together so that they are able to work more closely, helps to identify mutual benefits for all within the business — often not visible when operating in silos. The connection of these units means businesses can implement one data management strategy that in turn helps to reduce overall costs. When collaboration is combined with greater savings and opportunities, organizations are able to shorten their payback and increase return on investment.

Collaborating with outside consultants and suppliers also has its benefits. The acquisitions of these bodies means enterprises can seek advice on strategy, implementation and organisational change. Consultants can also advise or supply technology that can benefit and support overall data management requirements in an organisation.

For example, sports company ASICS was operating without a centralized, connected tracking system, and was grappling with timely collection and consolidation of its global sustainability data as it managed significant business growth in its retail operations. Schneider Electric helped the company overcome its data challenge by delivering consulting, software and implementation services. Reporting processes and data access improved dramatically, saving resources and allowing analysis and continuous enhancement of reporting further down into the supply chain.

Finally, working alongside NGOs or industry peers can also put enterprises in a better position to understand certain market insight and best practices. With peer-to-peer integration, the entire industry is able to take progressive steps forward and gain real insight into how to efficiently and effectively hit regulatory sustainability goals.

Put data into action

Having vast amounts of data doesn’t necessarily mean that organizations are reaping sustainability benefits. One of the main challenges of this data explosion is putting data into action. Firms must still act on the analysis if they are to see any benefits. Some key areas that are ripe for improvement are energy procurement, market forecasting, efficiency monitoring and benchmarking.

Once data is collected, it is important that it is centralized and available to a number of business units to allow for collaboration.

Contextualization is important when it comes to acting on data as well. When data is held in isolation it offers little value to forecasting goals and targets. However, when data is supported by information that adds internal and industry perspectives, it is much more manageable for enterprises to understand its credibility and potential. Organizations should add context to all data sets so they can establish accurate comparisons, patterns and predictions.

Verification is important once organizations have acted on the data. Decisions on efficiency and sustainability must be verified to correlate with an overall strategic vision. Organizations want to be able to support business cases with data and obtain the credibility that is deserved. Verification therefore helps to build longevity into future plans.

The firms that are willing to focus on the data-management challenge will benefit from new market opportunities. Enterprises should embrace data sets, and adopt a proactive and forward-thinking framework to reap the benefits of sustainability and efficiency. It is also key to engage in collaborative efforts with different business units or outside consultants to ensure data is managed closely and that correct actions are taken. Only when organizations consider these points can they truly seize the value of energy data.